AIMC Topic: Particulate Matter

Clear Filters Showing 31 to 40 of 234 articles

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

Environmental health perspectives
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...

Decoding PM oxidative potential in Ningbo, China: Key chemicals, sources, and health risks via dual-assay and machine learning.

Journal of hazardous materials
PM oxidative potential (OP), a key driver of health risks, was investigated in Ningbo, China, using dual dithiothreitol (DTT) and ascorbic acid (AA) assays combined with machine learning (ML). This approach accounts for the complexity of interactions...

Long-term exposure to PM and liver cancer mortality: Insights into the role of smaller particulate fractions.

Ecotoxicology and environmental safety
Particulate matter (PM) is a recognized carcinogen, but the effects of PM on liver cancer remain underexplored. This study investigates the long-term association between PM and liver cancer mortality, as well as the contribution of smaller particles ...

Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.

Environmental monitoring and assessment
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...

Epidemiological association and machine learning-based prediction of lung cancer risk linked to long-term lagged satellite-derived PM in China.

Frontiers in public health
OBJECTIVES: This study investigated association between long-term PM exposure and lung cancer incidence, focusing on Jiangsu Province, China. We aimed to explore the effects of historical PM with time lags and build a prediction model using machine l...

Low-Cost Particulate Matter Mass Sensors: Review of the Status, Challenges, and Opportunities for Single-Instrument and Network Calibration.

ACS sensors
As an emerging atmospheric monitoring technology, low-cost sensors for particulate matter of diameters below 2.5 μm (PMLCSs) supplement traditional air quality monitoring instruments. Because their stability and accuracy are typically low, they requi...

Machine learning-based quantification and separation of emissions and meteorological effects on PM in Greater Bangkok.

Scientific reports
This study presents the first-ever application of machine learning (ML)-based meteorological normalization and Shapley additive explanations (SHAP) analysis to quantify, separate, and understand the effect of meteorology on PM over Greater Bangkok (G...

Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling.

Environment international
Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on s...

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.

Environmental pollution (Barking, Essex : 1987)
There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmos...